Zero error coordination. - Mahed Abroshan; Amin Aminzadeh Gohari; Sidharth Jaggi (ITW Fall, 2015)

Codes for channels with segmented edits. - Mahed Abroshan; Ramji Venkataramanan; Albert Guillen i Fabregas (ISIT, 2017)

Multilayer codes for synchronization from deletions. - Mahed Abroshan; Ramji Venkataramanan; Albert Guillen i Fabregas (ITW, 2017)

Efficient Systematic Encoding of Non-binary VT Codes. - Mahed Abroshan; Ramji Venkataramanan; Albert Guillén i Fàbregas (ISIT, 2018)

Coding for Segmented Edit Channels. - Mahed Abroshan; Ramji Venkataramanan; Albert Guillen i Fabregas (IEEE Trans. Inf. Theory, 2018)

Coding for Deletion Channels with Multiple Traces. - Mahed Abroshan; Ramji Venkataramanan; Lara Dolecek; Albert Guillén i Fàbregas (ISIT, 2019)

Improving Fairness and Privacy in Selection Problems. - Mohammad Mahdi Khalili; Xueru Zhang; Mahed Abroshan; Somayeh Sojoudi (AAAI, 2021)

Fair Sequential Selection Using Supervised Learning Models. - Mohammad Mahdi Khalili; Xueru Zhang; Mahed Abroshan (NeurIPS, 2021)

Multilayer Codes for Synchronization From Deletions and Insertions. - Mahed Abroshan; Ramji Venkataramanan; Albert Guillén i Fàbregas (IEEE Trans. Inf. Theory, 2021)

An Information-theoretical Approach to Semi-supervised Learning under Covariate-shift. - Gholamali Aminian; Mahed Abroshan; Mohammad Mahdi Khalili; Laura Toni; Miguel R. D. Rodrigues (AISTATS, 2022)

Symbolic Metamodels for Interpreting Black-Boxes Using Primitive Functions. - Mahed Abroshan; Saumitra Mishra; Mohammad Mahdi Khalili (AAAI, 2023)

Loss Balancing for Fair Supervised Learning. - Mohammad Mahdi Khalili; Xueru Zhang; Mahed Abroshan (ICML, 2023)

Learning machines for health and beyond. - Mahed Abroshan; Oscar Giles; Sam F. Greenbury; Jack Roberts; Mihaela van der Schaar; Jannetta S. Steyn; Alan Wilson; May Yong (CoRR, 2023)

Revisiting DeepFool: generalization and improvement. - Alireza Abdollahpourrostam; Mahed Abroshan; Seyed-Mohsen Moosavi-Dezfooli (CoRR, 2023)

Conservative Policy Construction Using Variational Autoencoders for Logged Data With Missing Values. - Mahed Abroshan; Kai Hou Yip; Cem Tekin; Mihaela van der Schaar (IEEE Trans. Neural Networks Learn. Syst., 2023)

Imposing Fairness Constraints in Synthetic Data Generation. - Mahed Abroshan; Andrew Elliott; Mohammad Mahdi Khalili (AISTATS, 2024)

SuperDeepFool: a new fast and accurate minimal adversarial attack. - Alireza Abdollahpour; Mahed Abroshan; Seyed-Mohsen Moosavi-Dezfooli (NeurIPS, 2024)